Hacker News new | past | comments | ask | show | jobs | submit login

> Max pooling tests if a feature occurs anywhere in a certain area, rather than being sensitive to the exact location.

From Geoff Hinton's AMA on Reddit: The pooling operation used in convolutional neural networks is a big mistake and the fact that it works so well is a disaster.




Hinton doesn't like that pooling loses track of the exact locations where features are located, and just tests if a feature occurs in some area.

The basic effect of this is to decrease the resolution, so it's more tractable to operate on. Without pooling you are stuck with a huge resolution at each layer.




Join us for AI Startup School this June 16-17 in San Francisco!

Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: